1. AK Workshop Participant File Answer Key.R

## Exploratory Data Analysis:

## investigate the structure with str()

str(Census2020)


## see the columns of the dataframe and display a portion with glimpse()

glimpse(Census2020)


## explore the dimensions of the dataframe with dim()

dim(Census2020)


## look up the top and bottom rows of the dataset, with head() and tail()

head(Census2020)

tail(Census2020)


## display the column names with colnames() and names(), note the difference in return format

colnames(Census2020)

names(Census2020)

## row names

rownames(Census2020)


## explore the largest and smallest value of a column with min() and max()

min(Census2020$`2020 Census Resident Population`)

max(Census2020$`2020 Census Resident Population`)


## display the summary statistics with summary(), call the whole dataframe and one column

summary(Census2020)


## open the complete dataset in a new window with View()

View(Census2020)


## to identify a column within the dataset: df$colname

Census2020$State

Census2020$Pop

Census2020$year


## to identify an exact position within the dataset: df[row,col]   

Census2020[1,]

Census2020[,1]

Census2020[1,1]

Census2020[1,1:3]

Census2020[1:3,1:3]


## use the assignment operator to assign values/store data to an object: <-

CensusAL <- Census2020[1,1:3]

CensusCA <- Census2020[5, 1:3]

CensusPop <- Census2020[,2]

USPop <- sum(CensusPop)